glam/AUSTRIAN_ISIL_SESSION_CONTINUED_20251118.md

Austrian ISIL Extraction Session - Continued (2025-11-18)

Session Context

Resumed from previous session where we discovered a critical issue: the Austrian ISIL database actually contains 1,934 results, not just 223 as initially assumed.

Key Discoveries This Session

1. Database Structure Clarification

The "1,934 results" count is REAL and represents:

• ~223 main institutions (pages 1-23) WITH ISIL codes
• ~1,711 department/branch records (pages 24-194) MOSTLY with ISIL codes

2. Critical Bug Fixed in Extraction Pattern

Original Problem: Scraper regex required ISIL codes at the END of the name with a space:

^(.+?)\s+(AT-[A-Za-z0-9]+)$

This pattern matched:

• ✅ "Stadtarchiv Steyr AT-40201-AR" (ISIL code separated by space)

But MISSED:

• ❌ "Universität Wien | Bibliothek AT-UBW-097" (ISIL code embedded in hierarchical name)

Solution: Updated regex to match ISIL codes with hyphens and embedded in longer names:

^(.+)\s+(AT-[A-Za-z0-9\-]+)$

3. Re-scraping with Corrected Pattern

Actions Taken:

1. Stopped original scraper (was at page ~35, extracting 0 ISIL codes)
2. Updated scripts/scrape_austrian_isil_batch.py with corrected regex
3. Deleted pages 24-40 (scraped with old pattern)
4. Restarted scraping from page 24 with corrected pattern

Current Status (as of 15:15 PM):

• ✅ Pages 1-23: Original scrape (223 institutions, all with ISIL codes)
• ✅ Pages 24-32: Re-scraped with corrected pattern
• ⏳ Pages 33-194: Currently scraping (ETA: ~25 minutes)

File Changes Made

Updated Scripts

1. scripts/scrape_austrian_isil_batch.py:

   • Fixed ISIL code extraction regex to handle hyphens
   • Changed pattern to: AT-[A-Za-z0-9\-]+ (added hyphen)
   • Now captures embedded ISIL codes correctly

2. scripts/merge_austrian_isil_pages.py:

   • Updated to handle institutions WITHOUT ISIL codes (departments/branches)
   • Changed data structure to separate:
     • institutions_with_isil (main institutions)
     • institutions_without_isil (departments/sub-units)
     • all_institutions (combined list)
   • Added statistics tracking for both categories
   • Updated default end page from 23 to 194
   • Bumped format version to 2.0

3. scripts/check_austrian_scraping_progress.py (NEW):

   • Progress monitoring script
   • Shows pages scraped, institutions found, estimated completion time

Data Files

Current State:

• data/isil/austria/page_001_data.json through page_023_data.json - Original scrape (223 institutions)
• data/isil/austria/page_024_data.json through page_032_data.json - Re-scraped with corrected pattern
• data/isil/austria/page_067_data.json - Test scrape (will be overwritten)

Expected Final State (after scraping completes):

• page_001_data.json through page_194_data.json - Complete dataset
• ~1,934 total institutions (estimated)

Current Statistics

As of page 32:

• Pages scraped: 32/194 (16.5%)
• Total institutions: 294
• With ISIL codes: 283 (96.3%)
• Without ISIL codes: 11 (3.7%)

Estimated Final Count:

• Total institutions: ~1,940 (10 per page × 194 pages)
• With ISIL codes: ~1,870 (96%)
• Without ISIL codes: ~70 (4%)

What Happens Next

1. Complete Scraping (⏳ In Progress)

Command running in background:

nohup python3 scripts/scrape_austrian_isil_batch.py --start 24 --end 194 > austrian_scrape_v2.log 2>&1 &

Monitor progress:

tail -f austrian_scrape_v2.log
python3 scripts/check_austrian_scraping_progress.py

ETA: ~25 minutes (from 15:15 PM = complete by 15:40 PM)

2. Merge All Pages

Once scraping completes, merge all 194 pages:

python3 scripts/merge_austrian_isil_pages.py --start 1 --end 194

This will create:

• data/isil/austria/austrian_isil_merged.json
• With metadata about institutions with/without ISIL codes
• Separate lists for main institutions vs. departments

3. Parse to LinkML Format

Update scripts/parse_austrian_isil.py to handle:

• Institutions WITHOUT ISIL codes
• Hierarchical names (pipe-delimited: "Parent | Department | Sub-unit")
• Parent-child relationships (infer from hierarchical names)

Expected output:

• data/instances/austria_isil_main.yaml - Main institutions (~1,870 records)
• data/instances/austria_isil_departments.yaml - Departments/branches (~70 records)

4. Add Hierarchical Relationship Parsing

For institutions with pipe-delimited names like:

"Universität Wien | Bibliotheks- und Archivwesen | Fachbereichsbibliothek"

Extract:

• Parent: "Universität Wien"
• Department: "Bibliotheks- und Archivwesen"
• Sub-unit: "Fachbereichsbibliothek"
• ISIL code: "AT-UBW-097"

Link sub-units to parent institutions in LinkML:

parent_organization:
  name: "Universität Wien"
  # Attempt to resolve to ISIL code of parent

5. Geocoding & Enrichment

Once parsed to LinkML:

1. Extract city names from institution names (Vienna, Graz, Linz, Salzburg, etc.)
2. Geocode to lat/lon using Nominatim
3. Enrich with Wikidata Q-numbers where available
4. Generate GHCIDs

6. Update Documentation

When complete, update:

• AUSTRIAN_ISIL_SESSION_COMPLETE.md - Final completion summary
• CURATION_STATUS.md - Add Austria statistics
• PROGRESS.md - Update global dataset statistics

Lessons Learned

1. Always Verify "Database Discrepancies"

Initial Assumption: Website shows 1,934 but we only found 223, must be a display error.

Reality: Database pagination had gaps. Results continue at higher offsets with different record types (departments vs. main institutions).

Lesson: When scraping shows fewer results than database claims, investigate thoroughly before concluding it's an error. Test random high-offset pages.

2. Regex Patterns Must Account for Variations

Problem: ISIL codes appeared in two formats:

• "Institution Name AT-CODE" (space-separated, at end)
• "Parent | Department AT-CODE" (embedded in hierarchical name)

Solution: Expanded regex to handle both patterns and added hyphen support for codes like "AT-40201-AR".

3. Hierarchical Data is Valuable

The department/branch records (previously assumed to be "filler") are actually more valuable than we thought:

• Provide granular collection locations within large institutions
• Show organizational structure (university departments, archive divisions)
• Enable precise attribution for digitized materials

Technical Notes

ISIL Code Format Variations

Austrian ISIL codes follow these patterns:

• Simple: AT-STARG (letters only)
• With numbers: AT-UBW-097 (letters + numbers)
• With hyphens: AT-40201-AR (numbers + hyphen + letters)

Regex must handle: AT-[A-Za-z0-9\-]+

Hierarchical Name Parsing

Pipe-delimited names indicate organizational hierarchy:

Level 1 | Level 2 | Level 3 AT-CODE

Examples:

• 1 level: "Stadtarchiv Graz AT-STARG"
• 2 levels: "Universität Wien | Bibliothek AT-UBW-HB"
• 3 levels: "Universität Wien | Bibliotheks- und Archivwesen | Fachbereichsbibliothek AT-UBW-097"

Parser should:

1. Split on " | " delimiter
2. Assign hierarchical levels
3. Attempt to resolve parent institution by name

Data Tier Classification

All records are TIER_1_AUTHORITATIVE because they come from the official Austrian ISIL registry, even if:

• Missing ISIL codes (departments may not have individual codes)
• Hierarchical sub-units (still officially registered in system)

Schema Implications

Need to handle in LinkML:

• parent_organization field for sub-units
• organizational_level enum: "primary" | "secondary" | "tertiary"
• hierarchical_path list: ["Parent", "Department", "Sub-unit"]
• is_sub_unit boolean flag

Expected Timeline

Task	Duration	Status
Scraping pages 1-23 (original)	Complete	✅ Done
Discover extraction bug	Complete	✅ Done
Fix scraper & re-scrape pages 24-32	Complete	✅ Done
Scrape pages 33-194	25 minutes	⏳ In Progress (ETA 15:40 PM)
Merge all pages	1 minute	⏸️ Waiting
Parse to LinkML	5 minutes	⏸️ Waiting
Geocoding	10 minutes	⏸️ Waiting
Documentation	5 minutes	⏸️ Waiting
Total	~50 minutes	60% complete

Commands for Next Session

If scraping completes and session ends, resume with:

# 1. Check scraping completion
cd /Users/kempersc/apps/glam
tail -20 austrian_scrape_v2.log

# 2. Verify all pages scraped
ls -1 data/isil/austria/page_*.json | wc -l  # Should be 194

# 3. Merge all pages
python3 scripts/merge_austrian_isil_pages.py --start 1 --end 194

# 4. Verify merged data
cat data/isil/austria/austrian_isil_merged.json | jq '.metadata'

# 5. Parse to LinkML (update parser first to handle hierarchical names)
python3 scripts/parse_austrian_isil.py

# 6. Validate LinkML output
linkml-validate -s schemas/heritage_custodian.yaml data/instances/austria_isil.yaml

Questions for Next Session

1. Should we create separate YAML files for main institutions vs. departments?
2. How to handle parent-child relationships in LinkML when parent ISIL code is unknown?
3. Should departments without ISIL codes still get GHCIDs?
4. How to represent hierarchical organizational structure in RDF export?

Files to Review

• scripts/scrape_austrian_isil_batch.py - Updated regex pattern
• scripts/merge_austrian_isil_pages.py - Updated merge logic
• austrian_scrape_v2.log - Current scraping progress
• data/isil/austria/page_024_data.json - Verify corrected extraction

---

Session Update: Deduplication Verification (2025-11-18)

Critical Quality Check Performed

After completing the extraction and discovering 22 duplicate records, we performed a comprehensive metadata verification to ensure deduplication didn't lose unique information.

Question: Did we discard unique metadata when removing duplicates?

Answer: ✅ NO - All 22 duplicates were byte-for-byte identical

Verification Results

• Duplicates analyzed: 22 records (4 unique names)
• Metadata differences found: ZERO
• Data loss: NONE
• Deduplication accuracy: 100%

Key Findings

1. "Bibliothek aufgelöst!" (20 occurrences)

   • Only field: name
   • All 20 occurrences: Identical
   • ✅ Safe to deduplicate

2. 3 other institutions (2 occurrences each)

   • Only field: name
   • All occurrences: Identical
   • ✅ Safe to deduplicate

Documentation

• Detailed analysis: docs/sessions/AUSTRIAN_ISIL_MISSING_INSTITUTIONS_ANALYSIS.md
• Verification report: docs/sessions/AUSTRIAN_ISIL_DEDUPLICATION_VERIFICATION.md

Final Counts

• Database claim: 1,934 institutions
• Raw extraction: 1,928 records
• After deduplication: 1,906 unique institutions
• Duplicates removed: 22 (all verified identical)

Data quality: ✅ 100% metadata preservation confirmed

---

Session Status: ✅ COMPLETE
Extraction Status: ✅ All 194 pages scraped
Deduplication Status: ✅ Verified correct (no metadata loss)
Documentation Status: ✅ Complete with verification reports
Next Action: Parse to LinkML format with hierarchical relationship handling